Whisper Base Bengali
This model is a fine-tuned version of arun100/whisper-base-bn-3 on the mozilla-foundation/common_voice_16_0 bn dataset. It achieves the following results on the evaluation set:
- Loss: 0.2078
- Wer: 28.8185
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1568 | 1.72 | 500 | 0.2145 | 29.8350 |
| 0.1507 | 3.43 | 1000 | 0.2132 | 29.5594 |
| 0.1466 | 5.15 | 1500 | 0.2119 | 29.3576 |
| 0.1463 | 6.86 | 2000 | 0.2106 | 29.2927 |
| 0.1426 | 8.58 | 2500 | 0.2098 | 29.2220 |
| 0.139 | 10.29 | 3000 | 0.2093 | 29.1075 |
| 0.1373 | 12.01 | 3500 | 0.2087 | 29.0878 |
| 0.1362 | 13.72 | 4000 | 0.2084 | 28.9769 |
| 0.1333 | 15.44 | 4500 | 0.2081 | 28.9129 |
| 0.1332 | 17.15 | 5000 | 0.2079 | 28.8945 |
| 0.1363 | 18.87 | 5500 | 0.2078 | 28.8185 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0